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• W3078418744 abstract "Demands of foods have been increased in recent years for human and animal nutrition. Food supply chain management has been required to administer series of products and services in efficient ways for agriculture and food production to achieve customer satisfaction at the lowest cost. Agricultural systems have been changed during recent years, and have caused improvements in consumption and production patterns. However, there is not much research on supply chains of seeds (e.g., soybean) which have been produced in Canada. In this research, we propose a new mixed-integer linear optimisation formulation for a soybean supply chain network including multiple growers, farm facilities, distributors, and customers. The profit is maximised in the objective function. The application of the proposed formulation is discussed in Ontario in Canada using Google Maps. The mathematical model is developed by a unique possibilistic approach to include uncertain parameters. It is noticeable that uncertainty has been ignored in several papers in the food supply chain literature. Then, the proposed model is extended to a bi-objective model for the purpose of considering the organic practices (e.g., organic farming). The results of this research are discussed and analysed for the soybean supply chain network." @default.
• W3078418744 created "2020-08-24" @default.
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• W3078418744 date "2020-01-01" @default.
• W3078418744 modified "2023-09-24" @default.
• W3078418744 title "Design and optimisation of a soybean supply chain network under uncertainty" @default.
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• W3078418744 doi "https://doi.org/10.1504/ijbpscm.2020.10031447" @default.
• W3078418744 hasPublicationYear "2020" @default.
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